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In an optical fiber perimeter security system, due to the fact that a large quantity of samples are collected in the process of data acquisition, this heavy data burden inevitably degrades the efficiency and accuracy of intrusion recognition. Hence, it is urgent to remove the redundancy of the collected data records, which essentially requires to describe event features in a concise and proper way. In this paper, we propose a synthesized feature based intrusion recognition method, which is especially suitable to describing the fiber intrusion vibration signals with both wide bandwidth and high nonstationarity. Firstly, the all-phase filter bank characterized by large sidelobe attenuation and high flexibility of coefficient configuration, is employed to parallelly divide the input signal into multiple frequency channels, from which the power values can be accurately calculated. Secondly, the crossing rate of the input signal is combined with these power values to construct a synthetical feature vector, in which both the time-domain information and frequency-domain information are incorporated together. Finally, these synthetical feature vectors are fed into a radial-basis-function network based classifier to recognize 4 common intrusions (climbing, knocking, waggling and cutting). Essentially, the high efficiency of our proposed scheme lies in the parallel pipeline mode of the configurable filter bank and simple calculation of features, which facilitates speeding up the intrusion recognition. The high accuracy of our proposed scheme lies in two aspects: 1) the all-phase filter bank possesses small inter-channel interference, which helps to reduce the inter-coupling between output power values; 2) the synthesis of both frequency-domain information and time-domain information ensures the completeness of feature description. Experiments show that the sensing range of the proposed scheme can reach 2.25 km. Moreover, compared with the empirical mode decomposition based method, the proposed method not only improves the precision, but also significantly speeds up the recognition.
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Keywords:
- optical fiber perimeter security /
- intrusion recognition /
- synthesized features /
- filter bank
[1] Rangaswamy S, van Doorn E 2012 US Patent 8 232 878
[2] Girao P M B S, Postolache O A, Faria J A B, Pereira J M C D 2001 IEEE Sens. J. 1 322
[3] Gong H, Song H, Zhang S 2014 IEEE Sens. J. 14 777
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[6] Sun Q Z, Liu D M, Liu H R, He Y, Yuan J G 2006 Proc. SPIE 6344 63440K
[7] Sun Q Z, Liu D M, Liu H R, Shum P 2007 Proc. SPIE 6781 67814D
[8] Xie S R, Zhang M, Lai S R, Liao Y B 2010 Proc. SPIE 7677 76770A
[9] Jiang L H, Yang R Y 2012 J. Comput. 7 1453
[10] Juarez J C, Maier E W, Choi K N, Taylor H F 2005 IEEE J. Lightw. Technol. 23 2081
[11] Xie S R, Zou Q L, Wang L W, Zhang M, Li Y H, Liao Y B 2011 IEEE J. Lightw. Technol. 29 362
[12] Huang X D, Yu J, Liu K, Liu T G, Chen Q N 2014 IEEE Photon. Technol. Lett. 26 1956
[13] Liu L, Sun W, Zhou Y, Li Y, Zheng J, Ren B T 2014 Pattern Recognition (Berlin Heidelberg: Springer) pp595-603
[14] Mahmoud S S, Visagathilagar Y, Katsifolis 2012 Photon. Sens. 2 225
[15] Liu K, Tian M, Liu T G, Jiang J F, Ding Z Y, Chen Q N, Ma C Y, He C, Hu H F, Zhang X Z 2015 IEEE J. Lightw. Technol. 33 4885
[16] Li K Y, Zhao X Q, Sun X H, Wan S R 2015 Acta Phys. Sin. 64 054304 (in Chinese) [李凯彦, 赵兴群, 孙小菡, 万遂人 2015 物理学报 64 054304]
[17] Huang X D, Jing S X, Wang Z H, Xu Y, Zheng Y Q 2015 IEEE Trans. Signal Process. 64 1173
[18] Wang Z H, Huang X D 2009 All Phase Spectrum Analysis and Filtering Technology of Digital Signal (Beijing: Publishing House of Electronics Industry) pp14-31 (in Chinese) [王兆华, 黄翔东 2009 数字信号全相位谱分析与滤波技术 (北京:电子工业出版社) 第14-31页]
[19] Huang X D, Wang Y D, Liu K, Liu T G, Ma C Y, Chen Q N 2016 IEEE Photon. J. 8 1
[20] Huan H X, Hien T T H, Tue H H 2011 IEEE Trans. Neural Netw. 22 982
[21] Lyons W B, Ewald H, Lewis E 2002 J. Mater. Process. Technol. 127 23
[22] Huang X D, Wang Y D, Liu K, Liu T G, Ma C Y, Tian M 2016 IEEE J. Lightw. Technol. 34 5049
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[1] Rangaswamy S, van Doorn E 2012 US Patent 8 232 878
[2] Girao P M B S, Postolache O A, Faria J A B, Pereira J M C D 2001 IEEE Sens. J. 1 322
[3] Gong H, Song H, Zhang S 2014 IEEE Sens. J. 14 777
[4] Yu S Y, Sun S L 2008 Laser Infrared 34 345 (in Chinese) [于胜云, 孙胜利 2008 激光与红外 34 345]
[5] Fan Z M 2008 China Security Protection 3 42 (in Chinese) [樊治敏 2008 中国安防 3 42]
[6] Sun Q Z, Liu D M, Liu H R, He Y, Yuan J G 2006 Proc. SPIE 6344 63440K
[7] Sun Q Z, Liu D M, Liu H R, Shum P 2007 Proc. SPIE 6781 67814D
[8] Xie S R, Zhang M, Lai S R, Liao Y B 2010 Proc. SPIE 7677 76770A
[9] Jiang L H, Yang R Y 2012 J. Comput. 7 1453
[10] Juarez J C, Maier E W, Choi K N, Taylor H F 2005 IEEE J. Lightw. Technol. 23 2081
[11] Xie S R, Zou Q L, Wang L W, Zhang M, Li Y H, Liao Y B 2011 IEEE J. Lightw. Technol. 29 362
[12] Huang X D, Yu J, Liu K, Liu T G, Chen Q N 2014 IEEE Photon. Technol. Lett. 26 1956
[13] Liu L, Sun W, Zhou Y, Li Y, Zheng J, Ren B T 2014 Pattern Recognition (Berlin Heidelberg: Springer) pp595-603
[14] Mahmoud S S, Visagathilagar Y, Katsifolis 2012 Photon. Sens. 2 225
[15] Liu K, Tian M, Liu T G, Jiang J F, Ding Z Y, Chen Q N, Ma C Y, He C, Hu H F, Zhang X Z 2015 IEEE J. Lightw. Technol. 33 4885
[16] Li K Y, Zhao X Q, Sun X H, Wan S R 2015 Acta Phys. Sin. 64 054304 (in Chinese) [李凯彦, 赵兴群, 孙小菡, 万遂人 2015 物理学报 64 054304]
[17] Huang X D, Jing S X, Wang Z H, Xu Y, Zheng Y Q 2015 IEEE Trans. Signal Process. 64 1173
[18] Wang Z H, Huang X D 2009 All Phase Spectrum Analysis and Filtering Technology of Digital Signal (Beijing: Publishing House of Electronics Industry) pp14-31 (in Chinese) [王兆华, 黄翔东 2009 数字信号全相位谱分析与滤波技术 (北京:电子工业出版社) 第14-31页]
[19] Huang X D, Wang Y D, Liu K, Liu T G, Ma C Y, Chen Q N 2016 IEEE Photon. J. 8 1
[20] Huan H X, Hien T T H, Tue H H 2011 IEEE Trans. Neural Netw. 22 982
[21] Lyons W B, Ewald H, Lewis E 2002 J. Mater. Process. Technol. 127 23
[22] Huang X D, Wang Y D, Liu K, Liu T G, Ma C Y, Tian M 2016 IEEE J. Lightw. Technol. 34 5049
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